The Internet allows easy access to a wide range of information from anywhere. Individuals can access Web pages including text, images, videos, and other information using a Web browser via the Internet to search for and obtain desired information. Generally, a search of the Internet can be conducted via search engines, such as Google, provided by Google Inc., Mountain View, Calif., and Internet Explorer, provided by Microsoft Corporation, Redmond, Wash. However, search engines often return large numbers of search results that are time consuming to review. Search queries are not usually sufficient to filter the search results and unable to provide narrowed search results based on interests of the user. On the other hand, many Web pages display online advertisement of a third party while an Internet user is accessing to the Web pages. Online advertisement is usually arranged to display suitable advertisement for the Internet user based on the past browsing histories of the user. Thus, to display optimized search results and suitable advertisement for each Internet user, personalizing information for each Internet user has become an important feature for search engines and online advertisers, such as narrowing the search results or only providing advertisement based on characteristics of the Internet user, such as user interests and preferences.
Traditionally, for identifying user interests, an interest profile is manually created from surveys or questionnaires completed by a user, as well as collected from the user's search activities. For instance, an interest profile for a user can be created from queries entered by the user via a search engine or results provided in response to the user's search activity. Alternatively, an interest profile for a user can be automatically generated via user modeling by extracting and inferring a user's preferences from the user's general behavior while interacting with the Internet. For instance, a method of generating user interest profiles by monitoring and analyzing a user's access to structured documents, such as Web pages, is disclosed in U.S. Pat. No. 6,385,619 to Eichstaedt, et al. Hierarchically structured parts of a document, such as a title, an abstract, and a detailed description are classified into categories in a known taxonomy based on types of content viewed by the user in the document. The types of content are determined based on the text within the documents or classification of the document. The taxonomy tree uses an interest score or a weight associated with each category to measure the importance of the particular category to the user. The weight of a category is derived from the user's clicks on the various parts of the document. The user profile is adjusted based on the user's changing interest by injecting randomly selected documents outside of the scope of the current interest into the categories in the taxonomy tree. However, the method of user interest modeling only creates a user interest profile for implicit user interests based on the user's search histories via search engines and browsing histories. Further, the method uses a textual analysis of the documents for classifying documents in the taxonomy tree; however, the taxonomy is not usually clearly defined by the textual analysis.
Accordingly, there is a need for generating an interest profile for a user based on an explicit information that clearly and explicitly describes interests of the user.